In previous reports we have described our model for T2D pathogenesis. It builds on the foundational model (Topp et al, J. Theor. Biol. 2000; 206(4):605-19), which posited that moderate but persistent increases in blood sugar mediate negative feedback to increase insulin secretion by increasing beta-cell mass, either by increased replication or reduced apoptosis. However, if that increase fails to occur or is inadequate to restore normal glucose homeostasis, further increases in glucose raise it to a level where it becomes toxic to beta cells. Instead of negative feedback, there is then positive feedback, which causes a catastrophic loss of beta-cell mass and T2D. In addition to quantitative refinements to more accurately reflect the measured dynamics of T2D progression in humans and rodents, we included regulation of beta-cell function, in two distinct forms, in addition to mass. Data show that such changes are more rapid and more extensive than changes in mass, especially for humans, for whom beta-cell replication is very slow after adolescence. The model captures many key features of T2D progression, including the sudden deterioration of glucose control after a long period of gradual worsening (threshold behavior) and the fact that prevention is generally much easier than reversal, but drastic interventions, such as bariatric surgery and extreme caloric restriction can reverse established disease. The model has been further extended to track fasting and post-prandial glucose, rather than just average daily glucose, which is important because individuals differ in which aspect of glucose deviates first from normal. In addition, the model can be paused at any point during progression over years to simulate glucose tolerance tests, both oral (OGTT) and intravenous (IVGTT). One prediction arising from the OGTT simulations is that time to peak glucose is a leading indicator of T2D risk, independent of the conventional fasting and two-hour glucose concentrations. A delayed peak, which is generally a higher peak as well, is indicative of delayed insulin secretion, due to impaired delivery of new insulin granules to the plasma membrane of the beta cells. This prediction was tested by clinical colleagues Sumner and Chung using data from the Federal Women's Study (Publication #1. 2017 Report). We are currently using a longitudinal data set from the NIDDK Phoenix Branch to test the model predictions that time to peak can provide earlier indication of T2D risk than two-hour glucose and that the peak shifts progressively to the right as individuals progress. We have begun to use the model in reverse mode: instead of using metabolic parameters (insulin resistance and beta-cell function) to predict the future trajectory of glucose, we can use current glucose measurements to estimate insulin resistance and beta-cell function. Once these parameters are obtained, we believe it will be possible to use the model in forward mode to predict their future glucose levels. We have initiated collaborations to test these ideas using OGTT data from rats and self-monitoring (finger-stick) data from humans with T2D. In another modeling approach, we have worked with Dr. Sumner and Chung to evaluate why non-diabetic and pre-diabetic African-American women have higher insulin levels in spite of lower glucose levels. Using published models from the Bergman lab (Cedars Sinai Medical Center, Los Angeles), and the Cobelli lab (University of Padova, Italy), we have shown that the higher insulin results from reduced insulin clearance by the liver rather than increased insulin secretion from the beta cells. A paper is under review. Further study will be needed to determine whether the higher insulin levels or higher clearance rates contribute to the elevated T2D risk of African Americans, or whether the increased risk is in spite of higher insulin.